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  Multithreading is used for two main reasons; one is to increase throughput and/or decrease latency, and also increase scalability and other is to make the code more succinct, structured, and the separation of concerns.<BR>
  Using multithreading to increase throughput and decrease latency is very tricky. It is often counterproductive because it is not implemented right. Unfortunately, it is very hard to have a <I>generic</I> multithreading solution for all problems. It is heavily dependent on the nature of the problem and the hardware/software platform. That is why the multithreading solution in DataFrame is very tunable and requires careful user adjustments. I suggest to always start with a single thread and later when the system is working correctly experiment with multithreading. DataFrame gives you the tools and plumbing to do that.<BR>
  Also, watch this video: <a href="https://www.youtube.com/watch?v=WDIkqP4JbkE">Scott Meyers: Cpu Caches and Why You Care</a>
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  <BR><img src="https://github.com/hosseinmoein/DataFrame/blob/master/docs/LionLookingUp.jpg?raw=true" alt="C++ DataFrame"
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